Tracking vehicle locations in a parking lot for definitive display on a gui

ABSTRACT

A computer implemented method for displaying on a map a definitive image of precise locations of multiple mobile objects such as vehicles in a lot. The lot is mapped digitally to display precise locations of sub-areas of different types, such as parking and movement slots and their raw, approximate distances from vehicles are determined from approximate coordinates of vehicles obtained remotely. A data base of vehicle and sub-area types is established and a vehicle placement matrix is determined providing probabilities of respective sub-areas being occupiable by respective vehicles derived from business environment rules based on compatibilities of respective vehicle types with respect sub-area types. Raw, approximate distances of vehicles from sub-areas are divided by the probabilities to provided adjusted distances, sub-areas ranked by least adjusted distances and the respective vehicles placed in their top ranked sub-areas for more accurate display of location on a GUI.

FIELD OF THE INVENTION

The invention relates to tracking vehicle positions in a parking lot fordefinitive display on a GUI for the purposes of inventory management andinventory security.

BACKGROUND OF INVENTION

In the automotive and storage and distribution industries, effectiveinventory management applications are critical to daily operations,where locating vehicles, trailers, or other mobile inventory accuratelyand in a timely manner is critical to business success.

At automotive dealerships, both sales and service employees routinelysearch for vehicles. If a salesperson cannot locate a vehicle for aprospective customer to test drive within a timely manner, thesalesperson is less likely to sell a vehicle. On the service side, sincea service technician bills customers for time spent repairing a vehicle,any time spent locating a vehicle is lost revenue. If vehicles could befound more quickly, more technician time would be spent repairingvehicles, which would increase the revenue per service technician forthe dealership. In the retail automotive industry, lost vehicle salesand inefficient use of labor are the costs of not locating vehiclesaccurately and quickly.

In the storage and distribution industry, distribution centers maximizerevenue by quickly transloading containers to trailers, splittingcontainer loads amongst multiple trailers, and returning containers backto ports in a timely manner. Centers are typically penalized for delays,and earn more business from retailer and other customers if they areconsistently on-time. Similarly, warehouses maximize revenue by quicklytracking boxes and pallets for packing and shipping. Locating mobileobjects such as trailers, containers, boxes, and pallets accurately andquickly is critical to performing any of these tasks.

In fact, in both the automotive and storage and distribution industries,the problem of locating mobile objects increases in difficulty as afunction of the total number of objects in inventory and the number ofpossible locations.

Currently, inventory management applications display the locationinformation in a graphical form (on a GUI) of single or multiple objectsby showing an image, (typically a dot or other image representing theobject), against a background image of an entire map of the storagefacility. Multiple objects showing multiple images are not used oftenbecause of the difficulty of interpreting raw location information frommultiple objects, simultaneously. The object image is placed on thedigital map on the basis of raw (x,y,z) coordinates generated throughone or multiple underlying object location technologies, including GPS,RFID, RF, Ultrasonic, Acoustic, Infrared, and other technologies.

Depending on the precision of the underlying location technology, thereis a resulting error radius which is expected to circumscribe the actuallocation of the object. This error radius may vary based onenvironmental constraints, including signals being blocked by walls,buildings, other objects, or inclement weather. A user is expected toextrapolate the most likely actual location of the object, based on thedot image and the error radius.

However, particularly when groups of vehicles or other objects arecrowded together, the inherent location errors may result in multipleoverlaps and fuzzy images which can be difficult to interpret by anobserver and lead to errors in guessing actual locations which becometime consuming and costly.

For example, in a parking lot, if the vehicle being sought is blocked by2 other vehicles, an accurate multiple object display of all vehicleswould prepare the user to take the keys of all 3 vehicles in order toretrieve the vehicle being sought in a single step. Alternatively, in asingle object display, the obstructing vehicle would not be displayedand it would have been necessary for the user to have physically gone tothe vehicle, noted the 2 vehicles that are blocking the vehicle beingsought, returned to the building to pick up all 3 keys, and thenreturned to the vehicle to retrieve it, requiring an additional roundtrip.

Similarly, in a warehouse, if a user is searching for a single productthat is on one of multiple pallets located throughout the warehouse, theuser can choose to retrieve the pallet that is least encumbered by otherpallets. Alternatively, in a single object display, the user wouldarbitrarily choose a pallet, possibly requiring unnecessary time andwork to move other pallets out of the way before being able to retrievethe pallet being sought.

SUMMARY OF THE INVENTION

It is an object of the invention to ameliorate or eliminate theabove-mentioned disadvantages by providing, automatically, adefinitive/accurate, real time, GUI display of respective positions ofthe multiple vehicles or other multiple objects on the map of a parkinglot or mobile object facility.

Accordingly, the invention provides a computer implemented method toautomatically track/identify respective parking slots and movement slotsoccupied by respective individual vehicles of a group of vehiclescrowded together in a parking lot to enable definitive, real time,display of the vehicles' respective parking and movement slots on a GUI,comprising the steps of:

determining a set of business environment rules based on compatibilityof respective slots with respective vehicles for providing relativeprobabilities of occupation of respective slots by respective vehicles;

determining raw distances of respective vehicles from respective slots;

adjusting values of raw distances of respective vehicles from respectivepotential slots according to the respective probabilities ofoccupiability as determined by the business environmental rules so thatthe relative proximities of slots to respective vehicles increase withincreasing probabilities of occupationiability as compared with relativeproximities derived from the raw distances;

ranking the respective slots in order of most proximate to respectivevehicles, as derived from the adjusted values of raw distances and,

placing respective vehicles in respective top ranked slots for real-timedisplay on a GUI and, so that any slot occupying vehicles are replacedby more proximate vehicles and replaced vehicles are then placed insuccessively ranked slots.

Thus, once information concerning any different types and/or physicalstates of vehicles and different types of slots and the applicablebusiness rules are established and entered on the data base, thelocations of vehicles and other mobile objects in the lot can be trackedin real time and displayed definitively on the computer GUIautomatically, without need for additional user estimation orinterpretative guesswork.

The invention also provides A computer implemented method toautomatically track/identify respective locations occupied by respectiveindividual vehicles of a group of vehicles crowded together in a parkinglot to enable definitive, real time, display of the vehicles' respectivelocations on a GUI, comprising the steps of:

a) creating a digital map of a main area of a parking lot by identifyingsub-areas of the parking lot of different types comprising parking slotsand movement slots, potentially occupiable by vehicles; dividing theparking lot into a grid of cells so that respective slots are filled byat least one cell with each cell being in only a single slot;

b) determining a business environment rule for each type of slot basedon vehicle compatibility which provides a probability that a slot of aparticular type is occupiable by a vehicle;

c) determining precise positional coordinates of respective parkingslots and movement slots;

d) providing means for remotely identifying respective vehicles and forproviding approximate positional coordinates of each vehicle identified;

e) designating a vehicle and comparing the approximate positionalcoordinates of said designated vehicle with the precise positionalcoordinates of each slot, as provided by the digital map, to determinerespective raw distances therebetween;

f) calculating adjusted distances of the designated vehicle fromrespective slots by changing values of respective raw distances by afactor dependent on relative probabilities of respective slots beingoccupiable by the designated vehicle according to the business rule, sothat relative proximities of respective slots to the designated vehicleare increased with increasing probability, by comparison with relativeproximities derived from respective raw distances;

g) ranking the slots in order by least adjusted distances from thedesignated vehicle and, in the event of slots having equal highestranking, assigning a top rank to one of those equal highest rankingslots by one of random selection and other criteria;

h) when the top ranked slot is unoccupied by another of the vehicles,placing the designated vehicle in the top ranked slot and, when the topranked slot is occupied, comparing the adjusted distance of thedesignated vehicle from the top ranked slot and the adjusted distance ofthe occupying vehicle from the top ranked slot and placing the moreproximate of those vehicles in the top ranked slot;

i) when the designated vehicle is not more proximate than the occupyingvehicle repeating step h) for successively ranked slots until one of thedesignated vehicle is placed in a slot and all attempts to place thedesignated vehicle are exhausted;

j) when the designated vehicle is more proximate than the occupyingvehicle, replacing the occupying vehicle by the designated vehicle sothat the occupying vehicle returns to the group; and,

k) repeating the steps e)-j) for all remaining vehicles of the group.

Business rules may be based, for example on the size and type,temperature or velocity of vehicle or mobile object, and thecorresponding size and type of potential slots or sub-areas in thevehicle or mobile object proximity.

For example, where a box is the mobile object and its approximate/raw(x,y,z) coordinate would place it in mid air, the probability basedadjustment provided by the invention would place an image of a box onthe most likely shelf (a pre-defined sub-area).

Similarly, where a vehicle is the mobile object and its approximate/raw(x,y,z) coordinate would place it on a curb, in a building, oroverlapping another vehicle, the invention would place an image of thevehicle in the most likely parking slot. Further, the invention will notplace a large trailer in a small vehicle parking slot, or a vehicle thatis in-motion in a parking slot.

The invention provides the advantages of increasing the accuracy of thelocation estimate of the mobile object; decreasing the time required toactually physically locate the object, and reducing the burden on theuser to interpret location results. In particular, the last mentionedadvantage reduces the required acumen and burden of pro-activity of auser to physically locate objects.

The invention enables respective locations of groups of mobile objectscrowded together to be displayed clearly, simultaneously, and inreal-time. In a variety of applications, this allows users to use otherdisplayed objects as relative landmarks when physically in the lot,locating the desired vehicle, and also prepares the user to negotiateother objects that are obstructing access to a desired object.

The invention also enables users to view available or unoccupiedsub-areas on the map—available shelf space, open parking slots, etc.

It will be appreciated that mobile objects to be tracked includevehicles, trailers, shipping containers, shipping pallets, mobilehospital equipment, or other classes of mobile equipment. Pre-specifiedareas include parking lots, airports, seaports, wharfs, warehouses,campuses, hospitals, distribution centers, battlefields, or otherpre-specified areas. Sub-areas include parking slots, rooms, alcoves,bays, cells, lockers, docks, shelves, stalls, or subdivisions.

The method of the invention bridges the gap between various locationtechnologies, such as GPS, RF, RFID, Ultrasonic, Acoustic, Infrared, andother technologies, which generate a raw (x,y,z) coordinate for asingle, specific object, and a graphical user interface (GUI), wheremultiple objects are displayed in a parking slot, room, area, or otherdiscrete sub-area on a digital map.

According to another aspect, the invention provide a method forimproving mobile object resolution in a real time simultaneous displayof multiple mobile objects in specific sub-areas of a facility area on aGUI comprising the steps of:

measuring approximate respective distances of respective mobile objectsfrom respective potentially occupiable specific sub-areas;

formulating at least one business environment rule based on relativecompatibilites of respective objects with respective sub-areasindicative of relative probabilities of respective objects being foundin respective sub-areas;

modifying the measured distances in accordance with the relativeprobabilities to provide respective adjusted distances; and,

placing respective mobile-objects in respective sub-areas located atleast adjusted distances therefrom for display in the facility area onthe GUI.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow chart showing the steps involved in providing a digitalmap of a parking lot or other mobile object facility;

FIGS. 2 and 3 show, respectively, circular sub-areas defined by cells oflarger and smaller sizes, respectively;

FIG. 4 shows a diagonally extending, parallelogram shape, sub-area as aparking slot defined by cells;

FIG. 5 is a flow chart showing the steps involved in placing respectivevehicles or other mobile objects in respective sub-areas or parkingslots

FIG. 6 is a plan/map of a portion of a parking lot;

FIG. 7 is an enlarged view of a portion of the parking lot, showing theposition of a first car is it would potentially appear on a displaybefore adjustment by the business rules;

FIG. 8 is a similar view to FIG. 7, showing the position of the firstcar as it would actually appear on a display after adjustment byapplication of the business rules;

FIG. 9 is a similar view to FIG. 8, showing also the position of asecond car as it would potentially appear on a display before adjustmentby the business rules;

FIG. 10 is a similar view to FIG. 9, showing the position of the secondcar as it would actually appear on a display after adjustment by thebusiness rules;

FIG. 11 is a similar view to FIG. 10, also showing the position of athird car as it potentially would appear on a display before adjustmentby the business rules;

FIG. 12 is similar view to FIG. 11, showing the position of the thirdcar as it would actually appear on a display after adjustment by thebusiness rules;

FIG. 13 is a similar view to FIG. 7, but showing the positions of elevencars as they would potentially appear on a display before adjustment bythe business rules; and,

FIG. 14 is similar view to FIG. 13, showing the position of the elevencars as it would actually appear on a display after adjustment by thebusiness rules.

DESCRIPTION OF PARTICULAR EMBODIMENT

The implementation of the invention in this embodiment comprises twomain stages: first, the configuration of overall lot area, sub-areas,lots and vehicles or mobile objects; and second, the placement ofvehicles or mobile objects based on raw (x,y,z) coordinates as adjustedby business environment rules based on sub-area and mobile objectcompatibility, for definitive display on a screen at improvedresolution.

Firstly, as shown in FIG. 1, at step 1, the (2 or 3 dimensional) parkingspace to be digitized is surveyed. The borders of the space are theninput on a central server at step 2. At step 3, the error radius E ofthe vehicle location technology is input. At step 4 the shortestdimension of any sub-area is input for determining minimum requiredindividual cell size. (Cell will have square or cube shape for 2D or 3Dmap). At step 5, the various different physical types of the sub-areasare determined, (grass, building, movement slot, parking slot), togetherwith the appearances. At step 6, one or more groups/sets of cells areselected to define individual sub-areas/slots and, at step 7, the spaceis digitized and ready for real-time vehicle/object placement.

The implementation of the above steps will now be explained in greaterdetail:

First, the user specifies the overall area dimensions (x,y,z), theprecision of the vehicle location technology (E), and the shortestdimension of any sub-area to be defined in the system. Accordingly, agrid representing the pre-specified area, with each grid cell sized tomeet the shortest dimension of any sub-area is generated. For example,if a user plans to depict a 40 square meter circular grass area in themiddle of an overall 2 dimensional area measuring 400 square meters, theuser could specify the shortest dimension as either 1 meter, as in FIG.2, or as 0.25 meters, in FIG. 3. Clearly, when specifying a shorter“shortest dimension of any sub-area”, a user can create more realisticnon-square sub-area shapes.

Next, sub-areas are defined based on the shape of one or more gridcells, sub-area type, and sub-area appearance. Large sub-areas may takeup multiple cells and have irregular shapes. For example, in a 2dimensional grid representing a parking lot, a diagonal parking space isshaped as a parallelogram and occupies a total of 20 total cells, asshown in FIG. 3. Sub-areas are further defined by a specific type. Forexample, a sub-area may be characterized as a “refrigerated” area, “10ft restricted ceiling” area, or as a non-usage” area. In the examplebelow, the sub-area is a “parking” slot (as opposed to a “moving” slot).Sub-areas are also defined by appearance (which may be an imagespecified by the user), and will be depicted on screen accordingly. Onthe screen, the parking space will appear light gray in color with fourwhite lines outlining the four corners so that it appears to havesmooth, not jagged sides.

Typically, a parking slot is 10 feet wide and 18 feet long. Each gridcell represents 1 foot. Thus, this diagonal parking space is 10 cells inwidth, by 18 cells in length.

Prior to placing or assigning mobile objects (vehicles) to parkingslots/sub-areas, as indicated in FIG. 50, a database of mobile objectsidentity and characteristics is established.

As indicated at 51, an object placement matrix of the probability thatan object (vehicle) could be based in a sub-area, based on businessenvironment rules of compatibilities of sub-areas with objects isdetermined.

As indicated at 52, for a designated vehicle, the identity, approximatelocation and state is received from the location technology (e.g RFID orGPS),

As indicated at 53, a list of all eligible sub-areas/slots is collatedand their (raw) distances from the vehicle determined, (omitting orremoving those outside the selected error radius E).

As indicated at 54, the respective raw distances of the sub-areas/slotsare divided by their respective probabilites of accommodating thedesignated vehicle according to the business rules matrix and ranked inorder of closeness to the vehicle.

As indicated at 55, if the top ranked sub-are/slot is empty, the vehicleobject is displayed as located in that sub-are/slot as indicated at 56,but if the sub-are/slot is occupied the adjusted distances of thedesignated and occupying vehicles are compared, as indicated at 57, andif the designated vehicle is closer than the occupying vehicle (lessadjusted distance), the designated vehicle replaces the occupyingvehicle, as indicated at 58, and the algorithm is rerun for the removedvehicle by returning to step 53. If the adjusted distance of thedesignated vehicle is not less than the adjusted distance of theoccupying vehicle, the top ranked sub-area is removed from the list, asindicated at 59, and if any sub-areas remain, the designated vehicle issubjected to the test of 57, if the sub-area is occupied or, ifunoccupied, displayed therein as indicated at 56.

If no sub-areas remain, an error repot entry is made detailing thefailure to place the vehicle object as indicated at 60.

Aspects of the steps outlined above will now be described In moredetail, Vehicles or mobile objects to be placed in sub-areas are definedby shape of one or more grid cells, type, state, and object appearance.As with sub-areas, vehicle/mobile objects may take up multiple cells andhave irregular shapes. Vehicle/objects are also further defined byspecific types. For example, an object may require “cold-storage”, be a“high priority” object. vehicle/objects are further characterized bystate, which can vary over the life of a vehicle/object. For example, avehicle/object can be “in motion”, “stationary”, “overheated” or“overcooled”. Vehicle or object appearance is defined by an imagespecified by the user, and will be depicted on screen accordingly.

In constructing the object placement matrix, the user defines thelikelihood of placement of an object into a sub-area based on number andshape of grid cells of sub-area, sub-area type, number and shape of gridcells of object, object type, and object state. For example, a “vehicle”object that is in the “stationary” state is highly likely to be placedin a “vehicle parking slot” sub-area, is relatively less likely to beplaced in a “vehicle moving slot” sub-area, and is least likely to beplaced in a “non-usage area”. Each combination of a sub-area, object,and object state is defined by a percentage likelihood of placementbetween 0% and 100%, for example, as shown in the matrix below:

Object Placement Matrix - % Likelihood Object could be placed inSub-Area Large Small Large Small Vehicle - Vehicle - Vehicle - Vehicle -Sub-Areas Stationary Stationary In Motion In Motion Small Parking Slot5% 100% 3% 40% Large Parking Slot 100% 80% 75% 20% Small Movement 30%60% 50% 100% Slot Large Movement 60% 40% 100% 80% Slot Large Grass Slot10% 10% 10% 5% Building Slot 0% 0% 0% 0% *Individual values arecalibrated based on individual application

Objects are then registered to be tracked in the system. Each physicalvehicle object to be tracked is assigned a unique identifier, andclassified by object shape and type. When the location system reports anobject's location and, possibly, the object's state (which varies overtime based changing conditions and is measured by a sensor within thelocation system), it will reference the object's unique identifier.

As vehicle objects move, the location system sends 1) an object's uniqueidentifier, 2) the updated (x,y,z) coordinates, and 3) the object“state” based on location system information.

In the placement procedure, based on the precision variable entered bythe user in the configuration stage, the method of the invention willcreate a list of sub-areas that are within the precision radius (E) ofthe given (x,y,z) coordinate, based on a (raw) distance calculationbetween given coordinate and the centroid of the sub-area. Allsub-areas, regardless of type are included in this list. Next, thedistances are divided by the corresponding percentage in the objectplacement matrix to provide the adjusted distance. For example, if theraw distance of a large vehicle is 3 meters from a large grass slot, theadjusted distance would be 3/10%=30.

This list is now ranked in order of least adjusted distance. If multiplesub-areas have the same adjusted distance, they are ranked randomly inrelation to each other or by some other criterion such as firstconsidered.

If the top ranked sub-area is unoccupied, the object is placed in thatsub-area and the placement procedure terminates. If the top rankedsub-area is occupied, the adjusted distance of the existingvehicle/object is compared with the adjusted distance to the new object.If the new vehicle/object has a smaller adjusted distance, the newvehicle/object is placed in the sub-area, and the placement procedureruns again in order to place the existing object.

If the new vehicle/object is equally close or has a greater adjusteddistance, the existing vehicle object remains in the sub-area, and thenew vehicle/object is attempted to be placed in the second rankedsub-area. If the second ranked sub-area is unoccupied, thevehicle/object is placed in this sub-area and the placement procedureterminates. If the second top ranked sub-area is occupied, the inventionwill compare the adjusted distance of the existing vehicle object to thenew vehicle object. If the new vehicle/object has a smaller adjusteddistance, the new vehicle object is placed in the second top rankedsub-area, and the placement procedure runs again in order to place theexisting vehicle/object. If the new vehicle/object is equally close orhas a greater adjusted distance, the existing vehicle/object remains inthe sub-area, and placement of the new vehicle/object in the nexttop-ranked sub-area is attempted.

The procedure continues until the new vehicle/object has been placed andall displaced existing vehicle objects have been placed, or allsub-areas have been evaluated and an vehicle/object cannot be placed. Incase a vehicle/object cannot be placed, the invention creates an entryon an error report. This indicates to the user that either the precisionthreshold is too small, or that the sub-areas have not been definedaccurately.

In the case where the shape and size (by number of cells) of the objectis equal to or smaller than the shape and size of the sub-area where thevehicle is placed, the image of the object will be placed such that itfits within the boundaries of the sub-area, such that the centroid ofthe image is the same as the centroid of the sub-area.

In the case where the shape and size (by number of cells) of the objectis greater than the shape and size of the sub-area where the vehicle isplaced, the image of the object will be placed such that it minimizesthe total overhang over the boundaries of the sub-area. Thus, anelongate vehicle image will be displayed extending along the elongatemovement slot as shown in FIGS. 12 and 14, as otherwise the image wouldoverhang the slot boundary.

In the following examples, described in connection with FIGS. 6-14, thevehicle placement matrix is agnostic to vehicle size and vehiclevelocity. Additionally, all sub-areas forming slots are of the samesize. Only the top 2 slots (sub-areas) are considered within 25 m.

Object Placement Matrix Sub-Areas Vehicle - Stationary Vehicle - InMotion Parking Slot 100% 100% Movement Slot 10% 10% Grass Slot 5% 5%Building Slot 0% 0%Precise coordinates of respective parking slots S1-S8, and movementslots M1-M3, shown in FIGS. 6-14, are as follows:Parking Slots (centroids are in meters)

S1—(180,240) S2—(204,240) S3—(228,240) S4—(252, 240) S5—(180,288)S6—(204, 288) S7—(228, 288) S8—(252, 288) Movement Slots M1—(168,324)M2—(216, 324) M3—(264,324) Event 1

-   1. Car 1 has an approximate (raw) detected location of (215, 284)    which would correspond to a displayed position shown in FIG. 7    before adjustment by the business rules.

The top 2 slots are:

-   -   a. S6 (11.7 m adjusted distance index)    -   b. S7 (13.6 m adjusted distance index)

Car 1 therefore occupies S6, as shown in FIG. 8 as would be actuallydisplayed on the GUI.

Event 2

-   1. Car 2 has a position of (210, 292) which would correspond to a    displayed position shown in FIG. 9 before adjustment by the business    rules.

The top 2 slots are:

-   -   a. S6 (7.2 m adjusted distance index)    -   b. S7 (18.4 m adjusted distance index)

Car 2 displaces Car 1 to occupy S6 because it has a more favorable,(higher ranking), adjusted distance index, (7.2 m<11.7 m).

Re-run Algorithm for Car 1. Car 1 has a position of (215,284). The top 2slots are:

-   -   c. S6 (occupied by Car 2 which has a more favorable adjusted        distance index)    -   d. S7 (13.6 m adjusted distance index)

Therefore, Car 1 occupies S7 as shown in FIG. 10.

Event 3

-   1. Car 3 has position of (222,305) which would correspond to a    displayed position shown in FIG. 11, before adjustment by the    business rules.

The top 2 slots are:

-   -   a. S7 (occupied by Car 1 which has a more favorable adjusted        distance index, 13.6 m<18 m)    -   b. M2 (19.9 m/10%=199 m adjusted distance index)

Therefore, Car 3 occupies M2 in the actual, real time display, as shownin FIG. 12. In practice, car images will not have any identifiable frontfacing direction but are aligned with slot direction.

The following 11 vehicle example shows that the utility of the inventionis signific ant even in the setting of a small area of a larger lot.

FIG. 13 shows the potential appearance of the vehicles positions on ascreen before adjustment according to the business environment rules;and FIG. 14 shows the actual screen display after the adjustment placingthe cars in appropriate sub-areas/slots.

In the preferred mode, the location technology is RF based and uses theRSSI (Received Signal Strength Indicator) to estimate location. Thislocation technology has an expected error radius of 15 feet.

Each vehicle is assigned a battery powered radio-transceiver (tag),which is called a blind node (location is unknown). The blind node isbattery powered and hangs from the rear view mirror of the vehicle.During the assignment process, the vehicle identification number (VIN)is paired with the blind node's unique identifier and is uploaded to thecentral server.

The area has solar powered or hard-wired radio-transceivers installedthroughout the lot, called reference nodes (with known locations). Thetransceivers are all connected in a mesh-network style and send locationmessage updates to a central dongle. The dongle node connects to a PC,which in turn sends location information to a central server, whichparses the location information and displays vehicles on the digitallot.

When a blind node begins moving, the motion sensor triggers and sendsout a RF blast which is received and measured by the reference nodes inits immediate proximity. The references nodes, which are always on toreceive messages from blind nodes and route messages to the dongle, eachsend a message back to the blind node with the received signal strengthand their known (x,y) coordinates. The blind node then estimates its ownlocation. It then sends a message through the mesh network of referencenodes to the dongle with its estimated location and its “moving” state.The dongle in turn sends the information to the PC.

When a blind node stops moving, the motion sensor stops triggering andthe location process repeats. The blind node sends a message with itsestimated location and its updated “parked” state.

The central server, using the assignment information of each blind node,identifies the vehicle, its estimated location, and its state (in motionor parked).

A tag similar to the tag intended for the vehicle, is the AeroScout T3Tag, sold by AeroScout of Redwood City, Calif., web address:aeroscout.com, the disclosure of which is incorporated herein byreference, which includes identification of vehicle, position, motionand temperature detection.

Another application of the invention is in the mining industry. In suchapplication, the area comprises a mine or site and sub-areas compriseshafts, passes, stations, levels, and chambers.

Mobile objects to be located include drills, electric shovels, buckets,materials (such as coal, copper, iron, precious metals, etc.), trucks,bulldozers, trams, bins.

1. A computer implemented method to automatically track/identifyrespective locations occupied by respective individual vehicles of agroup of vehicles crowded together in a parking lot to enabledefinitive, real time, display the vehicles' respective locations on aGUI, comprising the steps of: a) creating a digital map of a main areaof a parking lot by identifying sub-areas of the parking lot ofdifferent types comprising parking slots and movement slots, potentiallyoccupiable by vehicles; dividing the parking lot into a grid of cells sothat respective slots are filled by at least one cell with each cellbeing in only a single slot; b) determining a business environment rulefor each type of slot based on vehicle compatibility which provides aprobability that a slot of a particular type is occupiable by a vehicle;c) determining precise positional coordinates of respective parkingslots and movement slots; d) providing means for remotely identifyingrespective vehicles and for providing approximate positional coordinatesof each vehicle identified; e) designating a vehicle and comparing theapproximate positional coordinates of said designated vehicle with theprecise positional coordinates of each slot, as provided by the digitalmap, to determine respective raw distances therebetween; f) calculatingadjusted distances of the designated vehicle from respective slots bychanging values of respective raw distances by a factor dependent onrelative probabilities of respective slots being occupiable by thedesignated vehicle according to the business rule, so that relativeproximities of respective slots to the designated vehicle are increasedwith increasing probability, by comparison with relative proximitiesderived from respective raw distances; g) ranking the slots in order byleast adjusted distances from the designated vehicle and, in the eventof slots having equal highest ranking, assigning a top rank to one ofthose equal highest ranking slots by one of random selection and othercriteria; h) when the top ranked slot is unoccupied by another of thevehicles, placing the designated vehicle in the top ranked slot and,when the top ranked slot is occupied, comparing the adjusted distance ofthe designated vehicle from the top ranked slot and the adjusteddistance of the occupying vehicle from the top ranked slot and placingthe more proximate of those vehicles in the top ranked slot; i) when thedesignated vehicle is not more proximate than the occupying vehiclerepeating step h) for successively ranked slots until one of thedesignated vehicle is placed in a slot and all attempts to place thedesignated vehicle are exhausted; j) when the designated vehicle is moreproximate than the occupying vehicle, replacing the occupying vehicle bythe designated vehicle so that the occupying vehicle returns to thegroup; and, k) repeating the steps e)-j) for all remaining vehicles ofthe group.
 2. The method according to claim 1 wherein, said at least onebusiness environment rule comprises at least one of slot size; vehiclesize; vehicle priority, vehicle type, vehicle velocity; slot surfacematerial; and slot function and location in the parking lot.
 3. Themethod according to claim 1 wherein, each adjusted distance iscalculated by dividing the corresponding raw distance by the probabilitythat the slot could be occupied by the designated vehicle.
 4. The methodaccording to claim 2 wherein, each adjusted distance is calculated bydividing the corresponding raw distance by the probability that the slotcould be occupied by the designated vehicle.
 5. The method according toclaim 2 wherein, the business rule comprises vehicle velocity andcomprising the step of providing motion detecting means for the vehicle.6. The method according to claim 5 wherein each adjusted distance iscalculated by dividing the corresponding raw distance by the probabilitythat the slot could be occupied by the designated vehicle.
 7. The methodaccording to claim 1 wherein only slots within a predetermined rawdistance of a designated vehicle are ranked.
 8. The method according toclaim 3 wherein only slots within a predetermined raw distance of adesignated vehicle are ranked.
 9. The method according to claim 6wherein only slots within a predetermined raw distance of a designatedvehicle are ranked.
 10. A computer implemented method to automaticallytrack/identify respective parking slots and movement slots occupied byrespective individual vehicles of a group of vehicles crowded togetherin a parking lot to enable definitive, real time, display of thevehicles' respective parking and movement slots on a GUI, comprising thesteps of: determining a set of business environment rules based oncompatibility of respective slots with respective vehicles for providingrelative probabilities of occupation of respective slots by respectivevehicles; determining raw distances of respective vehicles fromrespective slots; adjusting values of raw distances of respectivevehicles from respective potential slots according to the respectiveprobabilities of occupiability as determined by the businessenvironmental rules so that the relative proximities of slots torespective vehicles increase with increasing probabilities ofoccupationiability as compared with relative proximities derived fromthe raw distances; ranking the respective slots in order of mostproximate to respective vehicles, as derived from the adjusted values ofraw distances and, placing respective vehicles in respective top rankedslots for real-time display on a GUI and, so that any slot occupyingvehicles are replaced by more proximate vehicles and replaced vehiclesare then placed in successively ranked slots.
 11. A computer implementedmethod to automatically track/identify respective locations occupied byrespective individual mobile objects of a group of mobile objectscrowded together in a facility to enable definitive, real time, displayof the mobile objects' respective locations on a GUI, comprising thesteps of: a) creating a digital map of a main area of a facility byidentifying sub-areas of the facility of different types comprisingstorage slots and movement slots, potentially occupiable by mobileobjects; dividing the facility into a grid of cells so that respectiveslots are filled by at least one cell with each cell being in only asingle slot; b) determining a business environment rule for each type ofslot based on mobile object compatibility which provides a probabilitythat a slot of a particular type is occupiable by a mobile object; c)determining precise positional coordinates of respective storage slotsand movement slots; d) providing means for remotely identifyingrespective mobile objects and for providing approximate positionalcoordinates of each mobile object identified; e) designating a mobileobject and comparing the approximate positional coordinates of saiddesignated mobile object with the precise positional coordinates of eachslot, as provided by the digital map, to determine respective rawdistances therebetween; f) calculating adjusted distances of thedesignated mobile object from respective slots by changing values ofrespective raw distances by a factor dependent on relative probabilitiesof respective slots being occupiable by the designated mobile objectaccording to the business rule, so that relative proximities ofrespective slots to the designated mobile object are increased withincreasing probability, by comparison with relative proximities derivedfrom respective raw distances; g) ranking the slots in order by leastadjusted distances from the designated mobile object and, in the eventof slots having equal highest ranking, assigning a top rank to one ofthose equal highest ranking slots by one of random selection and othercriteria; h) when the top ranked slot is unoccupied by another of themobile objects, placing the designated mobile object in the top rankedslot and, when the top ranked slot is occupied, comparing the adjusteddistance of the designated mobile object from the top ranked slot andthe adjusted distance of the occupying mobile object from the top rankedslot and placing the more proximate of those mobile objects in the topranked slot; i) when the designated mobile object is not more proximatethan the occupying mobile object repeating step h) for successivelyranked slots until one of the designated mobile object is placed in aslot and all attempts to place the designated mobile object areexhausted; j) when the designated mobile object is more proximate thanthe occupying mobile object, replacing the occupying mobile object bythe designated mobile object so that the occupying mobile object returnsto the group; and, k) repeating the steps e)-j) for all remaining mobileobjects of the group.
 12. The method according to claim 11 wherein, saidat least one business environment rule comprises at least one of slotsize; mobile object size; mobile object type, mobile object state; slotsurface material; and slot function and slot location in the facility.13. The method according to claim 11 wherein, each adjusted distance iscalculated by dividing the corresponding raw distance by the probabilitythat the slot could be occupied by the designated mobile object.
 14. Themethod according to claim 12 wherein, each adjusted distance iscalculated by dividing the corresponding raw distance by the probabilitythat the slot could be occupied by the designated mobile object.
 15. Themethod according to claim 12 wherein, the business rule comprises mobileobject velocity and comprising the step of providing motion detectingmeans for the mobile object.
 16. The method according to claim 15wherein each adjusted distance is calculated by dividing thecorresponding raw distance by the probability that the slot could beoccupied by the designated mobile object.
 17. The method according toclaim 11 wherein only slots within a predetermined raw distance of adesignated mobile object are ranked.
 18. The method according to claim13 wherein only slots within a predetermined raw distance of adesignated mobile object are ranked
 19. The method according to claim 16wherein only slots within a predetermined raw distance of a designatedmobile object are ranked
 20. A method for improving mobile objectresolution in a real time simultaneous display of multiple mobileobjects in specific sub-areas of a facility area on a GUI comprising thesteps of: measuring approximate respective distances of respectivemobile objects from respective potentially occupiable specificsub-areas; formulating at least one business environment rule based onrelative compatibilites of respective mobile objects with respectivesub-areas indicative of relative probabilities of respective mobileobjects being found in respective sub-areas; modifying the measureddistances in accordance with the relative probabilities to providerespective adjusted distances; and, placing respective mobile objects inrespective sub-areas located at least adjusted distances therefrom fordisplay in the facility area on the GUI.
 21. A method for improvingvehicle resolution in a real time simultaneous display of multiplevehicles in specific sub-areas of a lot on a GUI comprising the stepsof: measuring approximate respective distances of respective vehiclesfrom respective potentially occupiable specific slots of the lot;formulating at least one business environment rule based on relativecompatibilites of respective vehicles with respective slots indicativeof relative probabilities of respective vehicles being found inrespective slots; modifying the measured distances in accordance withthe relative probabilities to provide respective adjusted distances;and, placing respective mobile-vehicles in respective slots located atleast adjusted distances therefrom for display in the lot on the GUI.22. A method according to claim 1 in which, when a shape and size of avehicle is no larger than a shape and size of a slot in which thevehicle is placed, an image of the vehicle is positioned withinboundaries of an image of the slot, such that the vehicle image has acentroid which is coincident with a centroid of the slot image; and whena shape and size of the vehicle is greater than a shape and size of aslot in which the vehicle is placed, an image of the vehicle will bepositioned in the slot image to minimize any total overhang overboundaries of the slot image.
 23. A method according to claim 10 inwhich, when a shape and size of a vehicle is no larger than a shape andsize of a slot in which the vehicle is placed, an image of the vehicleis positioned within boundaries of an image of the slot, such that thevehicle image has a centroid which is coincident with a centroid of theslot image; and when a shape and size of the vehicle is greater than ashape and size of a slot in which the vehicle is placed, an image of thevehicle will be positioned in the slot image to minimize any totaloverhang over boundaries of the slot image.
 24. A method according toclaim 11 in which when a shape and size of a mobile object is no largerthan a shape and size of a slot in which the mobile object is placed, animage of the mobile object is positioned within boundaries of the animage of the slot, such that the mobile object image has a centroidwhich is coincident with a centroid of the slot image; and when a shapeand size of the mobile object is greater than a shape and size of a slotin which the mobile object is placed, an image of the mobile object willbe positioned in the slot image to minimize any total overhang overboundaries of the slot image.
 25. A method according to claim 20 inwhich when a shape and size of a mobile object is no larger than a shapeand size of a sub-area in which the mobile object is placed, an image ofthe mobile object is positioned within boundaries of an image of thesub-area, such that the mobile object image has a centroid which iscoincident with a centroid of the sub-area image; and when a shape andsize of the mobile object is greater than a shape and size of a sub-areain which the mobile object is placed, an image of the mobile object willbe positioned in the sub-area image to minimize any total overhang overboundaries of the sub-area image.